Accurate indoor localization using a satellite based Global Positioning System (GPS) is difficult to achieve because the GPS signals are attenuated when the signals propagate through obstacles, such as roof, floors, walls and furnishing Consequently, the signal strength becomes too low for localization in indoor environments.
A number of methods and systems are known for indoor localization. Most prior art techniques require that specialized hardware is installed in the environment. Although those methods achieve accurate localization, the necessity for installing the hardware is seen as a huge disadvantage from cost, maintanance and complexity perspectives.
Methods that solely rely on conventional Wi-Fi chipsets for indoor localization use measured received signal strength (RSS) levels obtained from the Wi-Fi chipsets. Most of the prior art techniques require training, which includes measuring the RSS levels offline in the indoor environment. These measurements are then supplied to the localization method during online use.
The main limitation associated with the training is in that the offline measurements are unreliable. This is because the RSS levels in the environment vary dynamically over time, for example, due to changes in the number of occupants, the furnishing and locations of the APs. This implies that the training needs to be repeated whenever the environment changes.
U.S. Pat. No. 7,317,419 describes a method for localizing a target device at an unknown location based on the RSS measurements obtained at sensors whose locations are known. The method utilizes a path loss model, where a value of path loss exponent depends on the distances between the transmitter and receiver and some features of the indoor environment.
U.S. Pat. No. 8,077,090 describes a method in which mobile devices report the RSS values to a central server and, if available, a GPS based location estimate. The central server constructs a radio map of an indoor environment. Path loss coefficients, transmitted powers and locations of a number of devices are determined simultaneously by solving a system of equations. The number of access points needs to be large enough to support estimation of large number of parameters.
U.S. Publication 20120129546 uses a difference between the RSS measurements obtained at two consecutive locations to infer the most probable path traversed between these two points. Different constraints on path can be imposed.
U.S. Pat. No. 8,879,607 describes a method that performs indoor localization using the path loss model and RSS measurements at Rake receiver. The receiver extracts the strongest arrival and assigns path loss coefficient corresponding to a free space propagation. There is also a possibility of setting the path loss coefficient corresponding to the strongest arrival based on the type of the building and carrier radio frequency.
U.S. Pat. No. 8,264,402 describes a method that performs indoor localization using the RSS measurements and path loss model. The locations and reference signal levels of the access points are known and used to calibrate path loss coefficients between access points. Thus obtained path loss coefficients are used in some weighted sums to estimate path loss coefficients between an unknown location and access points. The unknown location is finally estimated from the obtained path loss coefficient and measured RSS levels.
Therefore, it is desired to perform RSS based localization in an unsupervised manner, i.e., without training.